Hiring of Consultant Firm for Target Group Identification and Audience Analysis

Hiring of Third-Party Verification Firm for Trigger 1 (Equity): Financial phasing model for more equitable budgetary allocations and to facilitate school-based hiring

Hiring of Consulting firm for technical support to strengthen ECE continuous professional development under GRADES-Baluchistan

Hiring of Third Party Validation (TPV) Firm for the Verification of Performance Based Conditions (PBCs)

Expected Outcome: Projects are expected to contribute to all the following expected outcomes: Effective and innovative methods for gathering, sharing and using large data sets in energy applications for the purpose of training AI models while ensuring privacy and security. Advanced and - wherever possible - open-source AI foundation models to support the digitalisation of the energy system, through improved grid observability, forecasting of supply and demand, advanced storage and renewables integration, demand side flexibility and energy efficiency. Enhanced cooperation, knowledge sharing and interoperability among energy system actors for secure and seamless data exchange. Advanced methodologies for AI model development ensuring that the results are FAIR (Findable, Accessible, Interoperable, Reusable) beyond the project ending, open source and accommodating for technology evolution. Scope: The quality of AI models depends strongly on the amount, quality, and representativeness of the data used for their training. Projects are expected to focus on developing, training and testing AI foundation models, using extensive data sets to accelerate the energy transition in key focus…

Expected Outcome: Projects under this topic will contribute to the following outcomes: Accelerate market expansion for European deep tech startups across EU regions and beyond by fostering collaboration and mutual support among European deep tech startup ecosystem actors; Interconnect top-tier tech startup and scaleup hubs embedded in research, technology and higher education ecosystems; Enable cross-border access to infrastructures, facilities, corporates, investors and talents to deep tech startups and scaleups, including those funded by the European Innovation Council (EIC); Enable more European deep tech startups, including women-led startups and scaleups, to succeed scaling into globally competitive companies; Strengthen less-connected innovation hubs by integrating them into a Europe-wide collaborative network; Boost private and public investment in deep tech ventures established within the participating innovation hubs. Scope: This action builds upon the EU’s strategic vision outlined in the EU Competitiveness Compass [1] , the EIC scaling strategy [2] , and the EU Startup and Scaleup Strategy [3] . It aligns with the objectives of strengthening Europe’s deep tech…

Expected Outcome: Project results are expected to contribute to some or all of the following expected outcomes: Improved skills, tools and training curricula for Police Authorities in Europe and Civil Society Organisations (or Non-Governmental Organisations) to work with at-risk groups to prevent persons from going missing. Those improved skills, tools and training curricula are to take into account European multicultural dimension, as well as legal and ethical rules of operation; Enhanced investigation tools and methodologies for Police Authorities in Europe to tackle cold cases in the context of missing persons, based on modern (forensic) technologies and criminology; Modern training curricula for Police Authorities, their improved cross-border cooperation and enhanced tools and methodologies to tackle new cases of missing persons; Enriched European common approaches applied by Police Authorities in Europe to fight the issue of missing persons relying on the synergy of technology, the latest socio-psychological knowledge learned from cases, as well as field experience of Police Authorities and entities dealing with victims, while fully respecting fundamental rights such as…